Projected exposure of terrestrial vertebrates to different extreme climate events reveals high vulnerability to multiple hazards
Bibliographic record
Abstract
Climate change is intensifying extreme climate events, fundamentally altering ecosystem disturbance regimes. Impacts on biodiversity are typically assessed using climate model outputs (i.e., temperature, precipitation) or by focusing on one type of extreme event. For this study, we used a new dataset covering four climate extremes (droughts, heatwaves, river floods, and wildfires) derived from the output of five climate models and six climate impact models for future projections under three climate scenarios (SSP1-2.6, SSP3-7.0 and SSP5-8.5) from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP Phase 3b). We assessed the exposure of 33,936 terrestrial vertebrate species (amphibians, birds, mammals, and reptiles). We also compiled published evidence on how species respond to extreme events. Heatwaves emerged as the most prevalent threat, with over 70% of species' geographic ranges projected to be exposed by 2050 (SSP3-7.0 scenario) - a 60% increase from 2000 levels. More than 21,000 species face heatwave exposure in 75% of their range. Wildfire exposure is projected to affect more than 20% of species ranges by 2050, increasing to 30% by 2085, with more than 5,000 species exposed in 50% of their range by mid-century. Notably, our findings indicate substantial multi-hazard exposure, with approximately 30% of species’ geographic ranges facing at least two types of extreme events by 2050. Hotspots are species-rich areas in the tropics. More than 70 species, mostly amphibians and reptiles, are projected to be exposed to a high frequency of three types of events over 75% of their range. Most of these species already have declining populations and are listed as threatened on the IUCN Red List of Threatened Species. Our study highlights the importance of studying the impacts of extreme events on biodiversity in a multi-hazard context. The combination of high exposure with documented negative impacts - such as heat stress mortality, reproductive failure, or wildfire injury – is of particular concern for already threatened species. This underscores the urgency of developing targeted interventions for vulnerable species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".